Want to get hired at Cash App?

Staff Data Scientist Cash App Lending

Cash App

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Original Job Summary

Overview

It all started with an idea at Block in 2013. Cash App has evolved from a simple peer-to-peer payments product to a dynamic ecosystem offering financial solutions including lending, investing, and more. The Staff Data Scientist Cash App Lending role is embedded in the Commerce & Lending organization to derive insights that improve customer experience.

Responsibilities

You will:

  • Analyze large datasets using SQL and scripting languages to surface actionable insights.
  • Apply statistical and mathematical modeling techniques to research customer behavior.
  • Design and analyze A/B experiments to assess product changes.
  • Collaborate with engineers to log new data sources and build curated ETL datasets.
  • Create data visualizations and self-serve dashboards for key stakeholders.
  • Communicate findings to team leads and cross-functional partners.

Qualifications

Direct experience in credit, lending, risk management, or financial services. Exceptional communication skills are required to explain complex technical concepts. Proven leadership in guiding cross-functional projects and influencing outcomes is essential. Advanced proficiency with SQL, data visualization tools, programming (Python or R), and a strong educational background in a STEM field are expected with 10+ years of experience (or 8+ years with a graduate degree).

Benefits & Culture

Cash App offers comprehensive benefits including healthcare, retirement plans, equity, paid time off, and learning & development resources. The company fosters a culture of innovation, collaboration, and inclusion with remote work options available worldwide.

Key skills/competency

  • Data Analysis
  • SQL
  • Python
  • Risk Management
  • Credit
  • Lending
  • A/B Testing
  • ETL
  • Data Visualization
  • Statistical Modeling

How to Get Hired at Cash App

🎯 Tips for Getting Hired

  • Customize your resume: Highlight data science and lending expertise.
  • Research Cash App: Understand company culture and innovation.
  • Showcase technical skills: Emphasize SQL, Python, and A/B testing.
  • Practice clear communication: Prepare to explain complex technical ideas.

📝 Interview Preparation Advice

Technical Preparation

Practice SQL queries on large datasets.
Refine Python coding for data processing.
Study statistical and machine learning models.
Review data visualization and ETL methods.

Behavioral Questions

Describe a time you led a project.
Explain how you influenced cross-functional teams.
Discuss challenges in explaining technical data.
Share experiences adapting in fast-paced settings.